R Notebook

Tmax = dim(df)[1]
t = 20
n_frames = Tmax/t #must pick something divisible

#make each transition point appear double 

#repeat every t^th twice so e.g. if t=20, get 1:20, 20:40 etc.
ind = sapply(1:n_frames, function(i){(t*(i-1)):(t*(i-1)+t)})
ind = ind[2:length(ind)] #remove extra 0
dfpad = df[ind,]

dfpad$frame =  c(rep(1,t),rep(2:n_frames, each = t+1))


plotly::plot_ly(data = dfpad,
                 x = ~eastwest, #~ so looks for them in dataset
                 y = ~northsouth,
                 frame = ~frame,
                 type = "scatter",
                 text = ~paste("Time:", Time),
                 mode = "lines+markers",
                 marker = list(size = 8,
                               symbol = "circle",
                               sizemode = "diameter"),
                 line = list(shape = "linear", width = 2)
                ) %>%
plotly::layout(xaxis = list(title = "East-West Direction"),
                 yaxis = list(title = "North-South Direction"),
                showlegend = F
        ) %>%
plotly::animation_opts(frame = 300,
                       transition = 10,
                       redraw = F) 

#TODO: would be cool to somehow represent the uncertainty
# Can get credible interval from posterior output, too...